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Abstract

This report outlines research work from May 1 to August 31, 1987.
It describes a function induction algorithm that is part of Peter Andreae's
robot procedure learning system NODDY. The report also describes a
C-Prolog implementation of this algorithm.
Two other systems that induce functions are BACON and COPER. Both are
discovery systems that determine empirical laws from observational
data. In addition to these systems, a general approach to symbolic
function induction is discussed.
This work was motivated by a desire to investigate the ramifications of
using a non-functional language such as Prolog to do function
inductions. The discussion focuses on the representation of
knowledge-in particular on the representation of inverse operators
and the induced expression-and the strength of argument typing.

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